A new learning theory integrates cognitive psychology and systems biology

Een nieuwe leertheorie integreert cognitieve psychologie en systeembiologie

Forms of learning. (a) Habituation. Hypothetical illustration, showing decreasing responses to repeated stimuli (arrows). For additional features, see [26]† (b) Sensitization. The opposite effect of habituation, which increases response. (c) Classical conditioning, adapted from [27, Box 1]† The right column shows whether a CR develops into the indicated CS. Protocol 1 is the traditional Pavlovian protocol in which the CS (CS1, blue bar), such as a tone or a light, is coupled to the VS (red star), shown here with a fixed delay from the start of CS. lyou and IC denote the US-US interval and the CS duration, respectively. In protocol 2, the US is randomly presented with equal chances to occur with or without the CS, and a CR does not develop. Protocols 3 and 4 are cue competition schemes involving multiple CSs. Protocol 3 has two phases: in the first phase, a CR is drawn up to CS1; in the second phase, the composite stimulus CS1+2 is presented with the VS, but a CR to CS2 does not develop. In protocol 4, CS1 is always presented as a connection to CS2 or CS3, and the US only occurs for CS1+2. A CR develops to CS2 presented separately, but not to CS1. In protocol 5, the CS is never linked to the US, but an inhibitory association is nevertheless created (see text). (d) Instrumental conditioning, with a Skinner box, in which an organism can receive pleasant (food) or unpleasant (shock) reinforcement, depending on its responses (lever) to different stimuli (light and tone); illustration taken from the Wikipedia article for Operant Conditioning Chamber under CC BY-SA 3.0 license. Credit: Procedures of the IEEE (2022). DOI: 10.1109/JPROC.2022.3162791

Many neuroscientists, medical researchers and engineers specializing in artificial intelligence have attempted to understand the neural mechanisms underlying learning. While studies have revealed some essential aspects of these mechanisms, many questions remain unanswered.

Jeremy Gunawardena, a researcher at Harvard Medical School, recently introduced a new view of learning that combines ideas from cognitive psychology with biological observations. His paper, published in Procedures of the IEEEhighlights some aspects of learning that can distinguish biological organisms from computers and machines.

“My interest in learning has partly arisen from a study we conducted earlier in which we showed that the unicellular protozoa, Stentor roeseli, exhibits a complex hierarchy of avoidance behavior when irritated by a beam of particles,” Jeremy Gunawardena, one of the researchers who conducted the study, told Phys.org. 1900 first described by American biologist Herbert Spencer Jennings, but it was considered non-reproducible.”

In their previous studies, Gunawardena and his colleagues showed that the Jennings’ findings were correct. More specifically, they found that a unicellular is potentially capable of much more complex learning behavior than previously thought possible.

Inspired by these findings, Gunawardena teamed up with one of his colleagues at Harvard, Sam Gershman, who has done extensive research on the mechanisms of learning. Their work specifically examined how learning takes place in individual cells

“The collaboration with Sam Gershman led to my research paper in Procedures of the IEEEGunawardena said. “The primary goal was to propose a definition of learning in information-theoretical terms that was not limited to animals like us, and to provide evidence from various domains in biology for the existence and significance of learning outside the nervous system

In his recent paper, Gunawardena describes learning as a broad and universal process involving all living systems, including various animal species, as well as potential plants. Thus, he believes that a reliable characterization and description of this process could inform research in various fields. For example, it could make a major contribution to the field of systems biology, and contribute to existing theoretical perspectives, which largely focus on molecules and their organization.

“We tend to think of cells as complex molecular machines,” Gunawardena said. “The idea that cells are able to learn – to form internal models of their external environment and use those models to guide their behavior – gives them a form of ‘agency’ that most machines lack and that brings us closer. at what it means to be “alive.” Finally, unraveling these ‘internal models’ could be very useful if we want to exploit cells in a therapeutic way, as we are trying to do in immunotherapy.”

If confirmed experimentally, the interesting ideas introduced by Gunawardena could provide a new and valuable perspective on how countless living organisms learn and survive. Several studies have already suggested that plants or specific cells, such as T cells (ie critical components of the immune system), can “learn” based on the stimuli they come into contact with.

“We now have to show that this perspective is real through the experimental work and this is what the collaboration with Sam Gershman is all about,” added Gunawardena. “Right now we are focusing on one of the simplest forms of learning, habituation, which is extremely commonly observed in biology, from animals like us to individual cells, and which exhibits a number of characteristic properties, despite vastly different underlying mechanisms. However, we still have no theory to explain this universality, nor do we have convincing explanations of how habituation works on the molecular levelthat’s what we’re trying to do now.”

Theory suggests that quantum computers should be exponentially faster at some learning tasks than classical machines

More information:
Jeremy Gunawardena, Learning Beyond the Brain: Integrating Cognitive Science and Systems Biology, Procedures of the IEEE (2022). DOI: 10.1109/JPROC.2022.3162791

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Quote: A New Learning Theory Integrating Cognitive Psychology and Systems Biology (2022, June 27) Retrieved June 28, 2022 from https://phys.org/news/2022-06-theory-cognitive-psychology-biology.html

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